Facilitating finance based on behavioral triggers

ABSTRACT

Systems and methods for facilitating finance by monitoring behavior of users indicative of behavioral patterns or deviations from behavioral patterns and inviting users to make financial changes that may be appropriate based on the monitored behavior. In some embodiments, a minimum amount of relevant data must be collected to support the existence of a behavioral pattern or deviation before a user is invited to make appropriate changes to their finances.

BACKGROUND

Consumers' financial needs can change for numerous reasons, such as theoccurrence of life cycle events relating to family, occupation, oreducation, as well as the occurrence of large purchases or purchasesthat require long term financial commitments.

SUMMARY

In accordance with certain aspects of the present disclosure, a systemfor facilitating finance is provided that infers changes in a user'sfinancial needs based on one or more triggering events, and invites theuser to perform one or more financial actions based on the inferredtriggering events.

In accordance with certain aspects of the present disclosure, a systemfor facilitating finance is provided, the system configured to monitor auser's behavior, infer one or more triggering events based on the user'sbehavior indicating possible changes in the user's financial needs,invite the user to perform one or more financial actions based on theone or more inferred triggering events, and execute one or morefinancial actions selected by the user in response to the system'sinviting.

In accordance with further aspects of the present disclosure, thebehavior monitoring takes places over extended periods of time, such asthree or more weeks, and a triggering event is not inferred until atleast a predetermined threshold amount of relevant data is collectedthat supports the inference.

In accordance with further aspects of the present disclosure, atriggering event can be a deviation from a pattern of behavior.

In accordance with further aspects of the present disclosure, atriggering event can be a new pattern of behavior.

In accordance with further aspects of the present disclosure, the systemmonitors behavior through one or more behavior tracking devices,including but not limited to a spending tracking device, a locationtracking device, a motion tracking device, a web activity trackingdevice, and a social media tracking device.

In accordance with further aspects of the present disclosure, thetriggers can be one or more of life cycle event triggers, large purchaseevent triggers, and long term financial commitment event triggers.

In accordance with further aspects of the present disclosure, thefinancial actions a first user of the system is invited to perform areselected by the system based on financial actions of other users of thesystem who have one or more attributes in common with the first user,including but not limited socioeconomic attributes.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example of a system forfacilitating financial transactions in accordance with aspects of thepresent disclosure.

FIG. 2 is a block diagram illustrating an example user device that canbe used in the system of FIG. 1.

FIG. 3 is a flow diagram illustrating an example of a processimplemented by the system of FIG. 1.

FIG. 4A is an example user interface display showing an example userinput screen in accordance with the system of FIG. 1.

FIG. 4B is another example user interface display showing an exampleuser input screen in accordance with the system of FIG. 1.

FIG. 4C is another example user interface display showing an exampleuser input screen in accordance with the system of FIG. 1.

FIG. 4D is another example user interface display showing an exampleuser input screen in accordance with the system of FIG. 1.

FIG. 5A is another example user interface display showing an exampleuser interface screen in accordance with the system of FIG. 1.

FIG. 5B is another example user interface display showing an exampleuser input screen in accordance with the system of FIG. 1.

FIG. 5C is another example user interface display showing an exampleuser input screen in accordance with the system of FIG. 1.

FIG. 6 is a block diagram illustrating portions of an example computersystem of the system of FIG. 1.

DETAILED DESCRIPTION

In the following Detailed Description, reference is made to theaccompanying drawings, which form a part hereof, and in which is shownby way of illustration specific embodiments which may be practiced. Thefollowing detailed description, therefore, is not to be taken in alimiting sense.

Features of the systems and methods for facilitating finance disclosedherein can benefit users of the systems/methods by making users aware ofappropriate financial opportunities and changes they may not otherwisehave been aware of. For example, people may undergo life cycle or majorfinancial changes in their lives not realizing that those changeswarrant a new or modified approach to their financial strategy. Inaddition, users of the system can have accounts with financialinstitutions for which revisions or updates to their accounts may beappropriate based on certain life changes, such as an address change,marriage, divorce, or a new child in the family. The system of thepresent disclosure infers when such financial changes may be appropriateand informs the user about the possible changes and why they may beappropriate. As a result, the users can save money they otherwise wouldnot have saved (e.g., by opening a college savings account for a child),earn money they otherwise would not have earned (e.g., by takingadvantage of a geographically-tied interest rate on savings as a resultof moving to a new geographical region), avoid missing payments they mayotherwise have missed (e.g., by signing the users up for automatic debitpayments when entering an agreement requiring periodic payments over along period of time), and also simplify and reduce the stress associatedwith making a variety of changes to their existing financial accountsettings, profiles, and other attributes.

Thus, the various computational components involved in the disclosedsystem are improved by the features and functionality of the disclosedsystems and methods.

FIG. 1 is a block diagram illustrating an example of a system 100 forfacilitating finance in accordance with aspects of the presentdisclosure. The system 100 includes a server 102 associated with afinancial institution (“FI”), e.g., a bank, and at least one device 104associated with a user of the system 100. The system 100 will typicallyhave a plurality of users, each of which is associated with a userdevice. As used herein a user can be any person or any other entity thatcan be associated with a financial account of the FI. The user device104 is configured to link to a financial account of the user (e.g., acredit card account, a checking account, a savings account, aninvestment account) that is associated with the FI. The FI server 102and the user device 104 interact via a data communication network(“network”) 106, e.g., the Internet.

The FI server 102 can include one or more computing devices configuredto operate together. The FI server 102 includes one or more databases108 and one or more modules containing instructions executable by acomputer processor, the one or more databases being accessible to theone or more modules. The modules can include, for example, a systemsubscription module 109, a behavior monitoring module 110, a triggermodule 112, a confirmation module 113, an action module 114, and anexecution module 115, which will be described in more detail below.

Various functionalities of the finance facilitation system disclosedherein can be carried out by one or more of the specifically enumeratedmodules disclosed, or alternatively by other modules of the system thatmay not be explicitly disclosed but are configured to carry out thedisclosed functionality. It should also be appreciated that the modulesneed not be executed by the FI server. For example, the system 100 caninclude its own dedicated server that executes the various functionalitymodules and that is not operated or managed by any user of the system orby any financial institution associated with the system, but that usersand financial institutions may nevertheless access via the system 100.

The one or more databases 108 contain information about the users of thesystem 100. For example, the one or more databases 108 can storeinformation about the users, such as their names, addresses, bankaccount information, spending history, location history, travel history,marital status and other family information, job and income information,or so forth. In some examples, the FI server 102 alternatively or inaddition is configured to access such information (when the FI has beengiven permission to do so) about one or more users of the system via thenetwork 106 from servers and databases outside of the FI, e.g., fromservers/databases associated with another financial institution or asocial media network. In still further examples, as discussed above, thesystem 100 can include its own dedicated server. Such a system-dedicatedserver can be linked to one or more system-dedicated databases that arenot operated or managed by any user of the system 100 or by anyfinancial institution associated with the system, but that users andfinancial institutions may nevertheless access via the system 100.Before access to such information can occur, in some examples theparty/server/database from which the information is accessed must firstgive permission to the financial institution or user of the system 100to access the information.

As discussed, each of the user devices 104 is associated with a user ofthe system 100 who holds at least one financial account with the FI,such that funds in that user's account with the FI can be added to orsubtracted from by executing actions enabled by the system 100. The userdevices 104 can be, e.g., a desktop computer, laptop computer, tablet,personal computer, smart phone, etc., that communicates over the network106 with the FI server 102 and/or other servers associated with thesystem 100. It should be appreciated that a single user of the system100 can be associated with multiple user devices that can be connectedto the system 100. The user device 104 includes a user interface 116.

The user interface 116 provides an interacting platform between the userand the system 100, e.g., with the FI server 102 or another server ofthe system 100. The user interface 116 can provide output provided by,and/or receive input required by, the system's various program modules,such as the behavior monitoring module 110, the trigger module 112, theconfirmation module 113, the action module 114, and the execution module115.

Optionally, the system 100 includes a third party server 120, which caninclude one or more of its own databases 122. The third party server 120can be associated with, e.g., a vendor, that provides goods or servicesto one or more users of the system. The database 122 can storeinformation pertaining to such goods and services and any accounts ofthe users of the system who purchase them. In some examples, the FIserver 102 can access data from and interact (e.g., send and receiveinstructions) with the third party server 120 via the network 106 inorder to coordinate one or more financial actions involving both a userof the system 100 and the third party, e.g., setting up automatic billpay between a user and the third party vendor.

The system subscription module 109 is configured to sign up users andoptionally, third parties, to use the system 100. As discussed, userscan be any persons or entities that hold one or more financial accountswith the FI. In addition, users can also include potential holders ofaccounts with the FI or others who have some relationship with the FIwithout actually holding a financial account with the FI. Thus, in someexamples, a new user of the system 100 can subscribe to the system 100(thereby becoming a new user) without holding any open financialaccounts with the FI, and the system 100 can essentially help the userdetermine if they would be interested in opening an account with the FI.Third parties can include vendors who provide goods or services to usersof the system.

The system subscription module 109 receives information about new usersof the system 100, including, e.g., user identifying information (suchas a name, address, phone number, facial photograph, email address),other user information (such as marital status, number and age ofchildren, occupation, income), and user permissions (e.g., parametersthat permit or deny access to additional information sources, such associal media accounts of the user, location devices associated with theuser, motion devices associated with the user, or the user's Internetactivity). The system subscription module 109 can create a unique loginfor the user to access the system 100 from the user's device (e.g., amobile device) and thereby access the user's account on the system 100.In addition, via the system subscription module 109, the user can linkone or more of the user's financial accounts managed by the FI to thesystem 100, such that the system can draw funds from, deposit fundsinto, or change information associated with, the user's financialaccount(s).

In some examples, a user of the system 100 downloads and installs asoftware application on a user device 104 that electronically links theuser device to the system 100, thereby enabling the user to access andprocess information from the system 100, as well as to enable the system100 to access information about the user. In addition, once a user logsin to the system 100, the system 100 can access one or more of theuser's financial accounts held by the FI in order to draw funds from,deposit funds into, or change information related to, the financialaccount(s).

The behavior monitoring module 110 is configured to monitor behavior ofusers of the system 100. In some examples, the system 100 is configured(e.g., by the FI) to monitor specific types of behavior. In addition, insome examples, the user of the system can set permissions (e.g., via thesystem subscription module 109) about what types of behavior may bemonitored by the behavior monitoring module 110. The behavior monitoringmodule 110 can access behavior information from or more sources ofinformation. Non-limiting examples of information sources include:financial accounts, which can provide information about a user's incomeand spending and saving behavior; social media accounts, which canprovide information about a user's life cycle changes; location devices,which can provide information about a user's location; motion sensingdevices, which can provide information about a user's motion; and webbrowser histories, which can provide information about a user's webbrowsing.

With respect to financial account information sources, the behaviormonitoring module 110 can, e.g., access data from users' financialaccounts with the FI. For example, the behavior monitoring module 110can track deposits and withdrawals into/from users' checking and savingsaccounts. Certain withdrawals or deposits could be indicative of a newbehavior pattern or a deviation from an old behavior pattern. Forexample, the cessation of automatic deposits from a user's employer intothe user's bank account could indicate that the user has lost their job.

With respect to social media accounts, the behavior monitoring module110 (if the FI is given permission to do so) can follow user profilesand written and pictorial posts and other interactions by the users ontheir social media accounts and glean information that could beindicative of a new behavior pattern or a deviation from an old behaviorpattern. For example, a change in relationship status in a user's socialmedia account from single or “in a relationship” to married couldindicate that a user has recently married or is planning to marry in thenear future.

With respect to location devices, the behavior monitoring module 110 (ifthe FI is given permission to do so) can track a user's location andglean information that could be indicative of a new behavior pattern ora deviation from an old behavior pattern. For example, if most of auser's time over the course of an extended period of time is spent in acity other than the one where the user is thought to live, this datacould indicate that the user has moved address.

Any suitable positioning device or system used in conjunction with theuser device 104 can be accessed by the system 100 and monitored by thebehavior monitoring module 110. Non-limiting examples of suchpositioning devices and systems include, e.g., global positioningsystems and devices, cellular tower triangulation, and Internet ofThings (IOT) devices, which can be used to track a user device 104 basedon its proximity to an object, e.g., a vehicle, or household applianceor other device with known location. Similarly, positioning or motiondevices can also detect when IOT devices have moved, which in some cases(such as the case of an Internet router), could indicate a new patternof behavior, such as moving home. Movement of other IOT devices, incontrast, such as a toothbrush, could be just as likely if not morelikely not to indicate a major new behavioral pattern, but rathersomething less significant such as a vacation or business trip. In someexamples, the positioning device locates the user device based on theuser device's connectivity to a particular Wi-Fi network, such as at auser's home or office, or the Wi-Fi network available at a store of athird party associated with the third party server 120. For non-mobileuser devices 104, the positioning device/system can operate, e.g., byidentifying an IP address associated with the user device, orassociating the user device with a particular Wi-Fi network or IOTobject. In some examples, the location of the user device can bedetermined when the user logs into, e.g., a social media account.

With respect to motion sensing devices, e.g., a pedometer installed inthe user device 104, the behavior monitoring module 110 can obtain datapertaining to other types of behavior patterns or deviations therefrom.For example, data showing that a user who used to walk several milesevery day is now walking much less could indicate that the user sufferedan injury or underwent surgery. In another example, a motion sensingdevice could provide data that a user has developed a pattern of drivingeach from a different address to their office than they used to,suggesting that the user has moved home or moved in with a significantother.

With respect to web browsing histories, the behavior monitoring module110 can track what websites the user visits and glean information thatcould be indicative of a new behavior pattern or a deviation from an oldbehavior pattern. For example, a user's visiting a large number ofcollege enrollment websites and web pages could indicate that the useror someone related to the user (e.g., a daughter or son) is going toenroll in college in the near future.

The behavior monitoring module 110 collects information related to thebehavior of the user, which information can be processed by the triggermodule 112 to infer one or more changes in the user's financial needsbased on the collected behavior information. In some examples, for agiven triggering event, the behavior must be monitored for an extendedperiod of time (e.g., three weeks or more) before sufficient data can becollected to support and inference of the triggering event.

In some examples, the trigger module 112 is configured to detectspecifically enumerated predefined triggering events (that are, e.g.,stored on the database 108) in the collected behavior information of theuser(s). For example, the trigger module 112 can be configured to detecta behavior pattern or deviation signifying the triggering event that auser has moved house or is considering moving house. In other examples,the trigger module 112 can be configured to detect behavior patterns ordeviations signifying the triggering events that: a user has recentlymarried or divorced; is going to marry or divorce in the near future;has recently had a baby or is going to have a baby in the near future;has a child that will be enrolling in college or graduate school in thenear future; may be interested in going on vacation in the near future;has made or is considering making a large financial commitment; has losta job or may soon lose a job; has sustained a major physical injury ormedical operation recently; or has opened an account or made a purchaseor may open an account or make a purchase in the near future requiringperiodic payments.

To detect a specifically enumerated pattern of behavior or deviationfrom a pattern of behavior, in some examples the behavior monitoringmodule 110 needs to have collected sufficient information from which toinfer the pattern or deviation. The threshold sufficiency of informationrequired by the trigger module 112 can be quantitative, i.e., at least apredetermined threshold amount of data is required, and/or qualitative,i.e., the cumulative data must reach or exceed a predetermined thresholdrelevance to the pattern or deviation in question. In addition, thepredetermined quantitative and/or qualitative data threshold(s) can varyamong specified predetermined behavior patterns and deviations. Itshould be appreciated that, in some cases, data relevance and quantityare intertwined; that is, the relevance of data increases as the numberof its occurrences increases.

For each enumerated behavior pattern or pattern deviation, the systemcan be configured to assign a relevance value to different types of datablocks, a data block being a discrete pre-defined set of data, such as auser's physical location at a given point in time or over a period oftime, or a user's child beginning their final year of high school.Another example data block is a user's large purchase or purchase of alarge number (e.g., ten or more) of a particular category of items, suchas home goods or furniture, which could indicate that a user is movingaddress. The system 100 can be dynamic, such that the relevance value ofdata blocks changes over time as the system 100 learns the predictivestrength of particular data blocks. The relevance value of data blockscan be user-specific, or based on collective information across allusers of the system or a subset of users of the system, e.g., a subsetthat has certain attributes (such as socioeconomic or geographicattributes) in common with the user in question.

For example, for a new user of the system 100, initial relevance valuescan be assigned to that user's data blocks based on collective relevancevalues ascertained from users system-wide, or from a subset of users whoshare one or more things in common with the new user, such as livingwithin a predefined distance of the new user, earning approximately thesame income as the new user, or having similarly aged children as thenew user. Once the initial relevance values are set for the new user,the system 100 can then automatically modify them based on the newuser's interactions with the system 100, the relevance values therebybecoming more specific to individual users themselves. It should also beappreciated that the relevance value assigned to one data block candepend on the other data blocks that have been collected by the behaviormonitoring module 110. For example, a certain data block may have zeroor low relevance in isolation, but substantial relevance in conjunctionwith the existence of one or more other data blocks.

In addition, in some examples there is a temporal component to therelevance value attached to one or more given data blocks. For example,the relevance value of a data block can decrease as time passes fromwhen the data was collected, reflecting the probability thatcircumstances or facts pertinent to the triggering event in questionhave changed since the data was collected.

Other non-limiting examples of factors that can affect the relevancevalue of a given data block include the time of year the data block iscollected, the likelihood that the reason for the data block isattributable to something other than the triggering event in question,the demographics attributable to the customer, or the behavior patternsof a user's friends and family members.

As discussed above, the relevance value assigned to a data block canalso be adjusted based on repetition and/or frequency of repetition ofthe existence of the data block. For example, a data block indicatingthat a user has visited a single car dealership in the past month may beassigned a low relevance value as far as predicting an automobilepurchase by that user, whereas a data block indicating that the user hasvisited car dealerships on five separate occasions in the past month maybe deemed highly relevant, i.e., indicative, that the user is planningto purchase an automobile. It should be appreciated that data blocks canbe defined in any number of ways. Thus, in the preceding example, thetrigger module 112 can process the user's five car dealership visits asfive low relevance events that add up to be highly relevant, oralternatively, as a single event assigned high relevance because of theunderlying repetition of the event.

By way of an illustrative example, the system 100 can be configured toassign relevance values (e.g., integer values between negative five andfive) to various data blocks in order to infer that a user of the systemhas moved from City A to a new address in City B. The system 100 assignsa relevance value of zero to a data block indicating that the user'schild is seventeen years old, effectively deeming this data blockirrelevant, or having zero predictive value, as to whether the user hasmoved to a new address in City B. The system 100 assigns a relevancevalue of five to a data bock indicating that the user has spent at leastthree-quarters of the nights during the past three months at the sameaddress in City B, deeming this data block highly predictive as towhether the user has moved to City B. The system assigns a relevancevalue of three to a data block indicating that the user has switchedsports teams affiliations to a team based in City B, deeming this datablock at least moderately predictive as to whether the user has moved toCity B. The system assigns a relevance value of negative two to a datablock indicating that someone has recently contacted the user via socialmedia expressing relief that the user decided to stay in City A for awhile longer, deeming this data block to have negative predictive valueof the triggering event that the user has recently moved or will bemoving soon to City B.

In some examples, therefore, the trigger module 112 processes datablocks and adds up the relevance values to determine if a triggeringevent has occurred, each triggering event requiring, in summation, atleast the predetermined relevance threshold of collected data.

In addition, it should be appreciated that relevance values can bespecific to the triggering event. Thus, a given data block can be morerelevant or less relevant depending on the triggering event. Forinstance, in the preceding illustrative example, although the data blockindicating that the user's child is seventeen years old was irrelevant(relevance value of zero) to the triggering event of the user's changingaddress, that data block could have a positive relevance value to atriggering event of the user having a child that may be attendingcollege in the near future.

In the preceding illustrative example, the system 100 could beconfigured to detect the triggering event (moving to a new address inCity B) when the sum of relevance values attributable to that triggingevent is, e.g., greater than or equal to seven. Thus, if at or about agiven time t₁ the trigger module 112 processes all the data blockspertinent to the triggering event of the user's moving from City A toCity B, and those data blocks include a data block indicating that theuser has spent at least three-quarters of the nights during the pastthree months at the same address in City B and a data block indicatingthat the user has switched sports teams affiliations to a team based inCity B, the sum of those relevance values (five plus three) exceeds thepredetermined relevance threshold, thereby triggering the event.

The trigger module 112 can be configured to process data blocks andrelevance values continuously, periodically, or in response topre-determined initiation events or instructions provided by the FI. Oneexample of an initiation event for a given triggering event is thecollection of any data block by the behavior monitoring module 110 thatcarries a positive relevance value for that triggering event. Anotherexample of an initiation event is a single data block having apre-assigned relevance value at or above the predetermined thresholdneeded to trigger the triggering event. For example, a social media postby a user of the system 100 stating their child will be starting collegeas a freshman in one month's time can initiate the trigger module 112 toprocess the data block associated with that social media post inconnection with the trigger event of a child going to college orgraduate school, the data block carrying sufficient relevance value totrigger the event all by itself.

As discussed, relevance values of data blocks can be specific to thetriggering event. Thus, the trigger module 112 can be configured toidentify different triggering events individually by processing datablocks on a triggering event by triggering event basis. In addition, thesystem 100 can be configured with a predefined set of enumeratedtriggering events for the trigger module 112 to detect. The predefinedtriggering events can be more or less specific than the examplesprovided in this disclosure. For example, a triggering event can be“change of address” and a more specific version of that triggering eventcan be “change of address to City B.”

As discussed, triggering events can include new behavior patterns orchanges to preexisting behavior patterns that suggest a user's financialneeds may be changing. Non-limiting examples of triggering eventsinclude: moving home; buying a new home; moving in with another person,e.g., a significant other; a child going to college or graduate school;a new child in the family; losing a job; starting a new job; gettingmarried; getting divorced or separated from a spouse; retiring;partially retiring (e.g., changing from full-time to part-timeemployment); making a large purchase (e.g., for an automobile, a boat, alarge animal such as a horse, a large medical expense such as surgery);or making a purchase requiring periodic bill payment over time.

The confirmation module 113 is an optional module configured to confirmwith the user that an inferred triggering event (i.e., a new behaviorpattern or deviation from a previous behavior pattern) has actuallyoccurred. In some examples, the confirmation module 113 is configured togenerate one or more questions that the user can answer via the userdevice 104. By answering the one or more questions generated by theconfirmation module, the user can effectively confirm that the inferredtriggering event has or has not occurred. For example, if the triggermodule 112 infers a triggering event that a user of the system 100 hasmoved in with another person, the confirmation module can cause the userdevice 104 to display a confirmation question, such as asking the userif they have recently moved in with another person. Via the user device104, the user can then submit an answer to the question confirming ordisconfirming the inferred triggering event.

The action module 114 generates one or more financial actions that auser of the system 100 can perform based on triggering events (i.e., newbehavior patterns or deviations from previous behavior patterns)detected by the trigger module 112, and present those one more actionsto the user via the user device 104 as executable financial actionoptions. In some examples, prior to generating the financial actionoptions, the action module 114 can cause the system 100 to learn moreabout the user's specific needs related to the triggering event, inorder to better tailor the financial action options that are generated.

Non-limiting examples of actions that may be appropriate and thereforegenerated by the action module 114 depending on the type of triggeringevent include: 1) filling out and submitting a change of address formfor one or more financial accounts, and associated actions; 2) opening anew financial account, e.g., a shared bank account or a college savingsaccount, and associated actions; 3) updating the FI's stored personalinformation about the user, e.g., the user's employer information, andassociated actions; 4) setting up a payment sharing plan (e.g., with anew roommate or significant other), and associated actions; 5) closingout one or more financial accounts and distributing the funds, andassociated actions; 6) setting up automatic bill payments to a vendor,and associated actions.

Associated actions, as used herein, can include, for example, suggestingand setting a meeting with a financial adviser (i.e., an employee of theFI), offering additional, related financial products to the user, and soforth.

The execution module 115 processes and executes the user's execution ofthe one or more financial actions generated by the action module 114 andselected by the user via the user device 104. In some examples, theexecution module 115 is also configured to process a user's declining toexecute any of the financial actions generated by the action module 114.For example, in response to receiving an instruction from the user viathe user device 104 that no financial actions are to be performed, theexecution module 115 can inform the system 100 accordingly, effectivelyterminating and/or deleting the relevant inferred triggering event.

FIG. 2 is a block diagram illustrating more details of the example userdevice 104 that can be used in the system 100 of FIG. 1. In the example,the user device 104 includes the user interface 116 as described above.In this example, the user device 104 includes an input device 130 and aplurality of behavior tracking devices 132 a and 132 b.

The user interface 116 allows the user to interface with the system 100,e.g., to answer questions, input information, receive triggering eventnotifications, and execute financial actions.

The input device 130 allows the user to input information orinstructions that can be sent to the system 100 via the network 106. Forexample, the input device 130 can be a touch user interface displayscreen, a voice command interface, a keyboard, a mouse, or another typeof input device installed on the user device 104.

The user device 104 can include any number of behavior tracking devices.In the example user device 104 of FIG. 2, the user device 104 includestwo behavior tracking devices 132 a and 132 b. A behavior trackingdevice can be any piece of hardware and/or software installed on theuser device 104 that can inform the system 100 (via the network 106)about a user's behavior patterns or deviations therefrom. Non-limitingexamples of behavior tracking devices include social media softwareapplications, Bluetooth®, web history trackers, global positioningdevices, pedometers, and other devices that determine the location ofthe user device 104 by Wi-Fi network proximity.

The user device 104 is configured to transmit behavior patterninformation from the one or more behavior tracking devices (132 a, 132b, etc.) via the network 106 to the FI server 102.

In some examples, one or more features of the system 100 becomeavailable only when enabled by the individual user of the system 100.For example, a user may have to open and/or login to a system accountresiding on the database 108 or to a particular software applicationresiding on the user device 104 in order for the FI server 102 tointeract with the user device.

FIG. 3 is a flow diagram illustrating an example of a behavioral triggerfinancial process 200 implemented by the system 100 of FIG. 1.

In a step 202, a user connects to the finance facilitation system 100 ofthe FI, e.g., by downloading a software application onto their userdevice and setting up a finance facilitation account (i.e., a useraccount) with the system 100, establishing settings, permissions,preferences, and the like. Authentication credentials, e.g., a loginname and password, security questions, etc., can be established tomitigate the chances of unauthorized access to the system 100 throughthe user's finance facilitation account. The user account is linked toat least one financial account of the user (e.g., a credit card accountor bank account). The financial account can be provided by the FI. Aspart of the step 202, the user can set permissions that link/provideaccess of the FI server 102 to one or more information sources, e.g.,social media accounts held by the user, location devices, etc., topermit the system 100 to monitor the user's behavior.

In a step 204 the behavior monitoring module 110 monitors the user'sbehavior and collects data blocks related to the user's behavior overtime.

In a step 206, the trigger module 112 processes collected data blocksand infers at least one triggering event corresponding to a behaviorpattern or a deviation from a behavior pattern of the user, and notifiesthe user, e.g., by causing the user device 104 to display a notificationthat it has inferred a triggering event.

In an optional step 208, one or more confirmation questions generated bythe confirmation module 113 are presented to the user via the userdevice 104 to confirm or disconfirm the occurrence of the inferredtriggering event.

In an optional step 210, the user confirms or disconfirms the inferredtriggering event.

If the user disconfirms the inferred triggering event, the process 200reverts to the step 204. If the user confirms the triggering event, in astep 212, one or more financial actions relevant to the triggering eventare generated by the action module 114 and presented to the user via theuser device 104. The user can choose to execute zero or more of thepresented financial actions.

If the user elects to execute zero of the financial actions, the process200 reverts to the step 204. If the user elects to execute one or moreof the financial actions, in a step 214 the one or more financialactions are executed by the execution module 115. As discussed above,execution of the one or more financial actions can require additionalinteractions and/or information provision from the user before thoseactions are completed.

It should be appreciated that multiple iterations of the process 200 forthe same user can run simultaneously, each iteration of the process 200corresponding to a different triggering event. For example, oneiteration of the process 200 can mine data related to a possible addressmove of the user, while another iteration of the process 200 can minedata related to the user's starting a new job.

FIGS. 4A-4D are example user interface displays showing user inputscreens on the user interface 116 of the user device 104 of FIG. 1.These user interface displays can be displayed to the user on the userdevice 104 in conjunction with the process 200 described above. In someexamples, these displays are generated when the process 200 utilizes thesteps 206, 208, 210, 212, and 214. Thus, the user interface displays ofFIGS. 4A-4D can be implemented following the system's inferring of atriggering event. The inferred triggering event at play in FIGS. 4A-4Dis a change of address into a shared living space (e.g., with a roommateor significant other).

In FIG. 4A, the user interface display 300 includes a notification 302that the system has inferred a behavior pattern/deviation triggeringevent that the user has changed address and moved in with anotherperson.

The user interface display 300 also includes a confirmation question304, and selectable options 306 and 308 allowing the user to confirm ordisconfirm the inferred triggering event by answering the confirmationquestion 304.

FIG. 4B shows an example user interface display 310 that can bedisplayed on the user's device 104 if the user confirms the triggeringevent by selecting the option 306 in FIG. 4A. FIG. 4B includes one ormore questions 312, the answer(s) to which can assist the system ingenerating appropriate financial actions for the user in question andthe triggering event in question. In this example, the question 312posed relates specifically to the triggering event and asks the user toidentify the type of person they have moved in with. In this example,the user interface includes selectable options 314, 316, and 318 foranswering the question, though it should be appreciated that other formsof data entry (e.g., a free form data entry field) would also beappropriate for answering the question(s). Once the user has submittedan answer to the question 312, the system can generate furtherinformation gathering questions and/or move on to generating appropriatefinancial actions.

FIG. 4C shows an example user interface display 320 that can bedisplayed on the user's device 104 after the user selected the option314 from the user interface display 310. The user interface display 320includes an invitation 322 for the user to perform one or moreselectable financial actions 324, 326, and/or 328 that may beappropriate as a result of the triggering event. The user interfacedisplay 320 also includes the selectable option 330 to perform nofinancial actions, and a selectable option 332 which prompts the system100 to generate and pose to the user additional selectable financialactions related to the triggering event. It should be appreciated thatthe selectable financial actions can be specifically tailored based oninformation known about the specific user. For example, the selectableoption 328 can mention only changing the address on a checking account,if the user does not have a savings account or credit card account withthe FI.

If the user ultimately elects to perform one or more financial actions,follow-on user interface displays can perform any steps required tocomplete those actions. One such example user interface 340 is shown inFIG. 4D, which could be a user-interface following the user's selectionof the selectable option 326 and, e.g., after the user identifies whichbill payments they would like to share with their roommate and thepercentage each party will be contributing to the payments. The userinterface 340 includes a prompt 342 asking the user to provideinformation about their new roommate, as well as data fields 344, 346,and 348 for the user to enter that information, and a submission button350 for submitting the information to the system 100 after it has beenentered.

FIGS. 5A-5C illustrate further example user interface displays showinguser input screens on the user interface 116 of the user device 104 ofFIG. 1. These user interface displays can be displayed to the user onthe user device 104 in conjunction with the process 200 described above.In some examples, these displays are generated when the process 200utilizes the steps 206, 208, 210, 212, and 214. Thus, the user interfacedisplays of FIGS. 5A-5C can be implemented following the system'sinferring of a triggering event. The inferred triggering event at playin FIGS. 5A-5C is the user's child's starting college.

In FIG. 5A, the user interface display 400 includes a notification 402that the system has inferred a behavior pattern/deviation triggeringevent that the user's son has started college.

The user interface display 400 also includes a confirmation question404, and selectable options 406 and 408 allowing the user to confirm ordisconfirm the inferred triggering event by answering the confirmationquestion 404.

FIG. 5B shows an example user interface display 410 that can bedisplayed on the user's device if the user confirms the triggering eventby selecting the option 406 in FIG. 5A. FIG. 5B includes one or morequestions 412 and 414 the answer(s) to which can assist the system 100in generating appropriate financial actions for the user in question andthe triggering event in question. In this example, the questions 412 and414 posed relate specifically to the triggering event and ask the userto provide information about how their son's college education is to befinanced. In this example, the user interface includes data fields 416and 418 for answering the questions, though it should be appreciatedthat other forms of data entry (e.g., selectable options) would also beappropriate for answering the question(s). Once the user has submittedan answer to the questions 412 and 414 (e.g., via the submit button420), the system can generate further information gathering questionsand/or move on to generating appropriate financial actions.

FIG. 5C shows an example user interface display 430 that can bedisplayed on the user's device after the user has entered all requiredinformation surrounding the triggering event in question. In thisexample, the user interface display 430 includes an explanation 432 asto why a particular financial action is recommended in view of thetriggering event in question. In this example, the explanation 432 wasgenerated by the system as a result of its data mining, e.g., via thebehavior monitoring module 110, of other users of the system 100 who maybe in the same or similar socioeconomic group as the user based onresidence neighborhood proximity, annual income, etc. The user interfacedisplay 430 includes an invitation 434 to execute the recommendedfinancial action (opening a college savings account), and selectableoptions 436 and 438 to execute or not to execute the recommendedfinancial action. If the user opts to execute the recommended financialaction, follow-on interface displays 430 can perform any steps requiredto complete the action, in this case, to open the college savingsaccount with the FI.

FIG. 6 schematically illustrates an example computer system suitable forimplementing aspects of the system 100 illustrated in FIG. 1, such asthe FI server 102, the third party server 120, and/or the user device104. The modules, databases, and other components of these servers anddevices could all be implemented on a common computer system, or thevarious components could be implemented on one or more separate computersystems that are accessible by one another. The computer 800, which maybe a server computer, for example, includes at least one centralprocessing unit (“CPU”) 802, a system memory 808, and a system bus 822that couples the system memory 808 to the CPU 802. The system memory 808includes a random access memory (“RAM”) 810 and a read-only memory(“ROM”) 812. A basic input/output system that contains the basicroutines that help to transfer information between elements within theserver computer 800, such as during startup, is stored in the ROM 812.The computer 800 further includes a mass storage device 814. The massstorage device 814 is able to store software instructions and data. Oneor more of the databases (e.g., the database 108) of the system could beimplemented by the mass storage device 814, or one or more of thedatabases could be implemented by other computer systems accessible bythe computer 800.

The mass storage device 814 is connected to the CPU 802 through a massstorage controller (not shown) connected to the system bus 822. The massstorage device 814 and its associated computer-readable data storagemedia provide non-volatile, non-transitory storage for the servercomputer 800. Although the description of computer-readable data storagemedia contained herein refers to a mass storage device, such as a harddisk or solid state disk, it should be appreciated by those skilled inthe art that computer-readable data storage media can be any availablenon-transitory, physical device or article of manufacture from which thecentral display station can read data and/or instructions.

Computer-readable data storage media include volatile and non-volatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer-readable softwareinstructions, data structures, program modules or other data. Exampletypes of computer-readable data storage media include, but are notlimited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid statememory technology, CD-ROMs, digital versatile discs (“DVDs”), otheroptical storage media, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe server computer 800.

According to various embodiments, the server computer 800 may operate ina networked environment using logical connections to remote networkdevices (such as the others of the FI server 102, the user device 104,and the third party server 120) through the network 820, such as awireless network, the Internet, or another type of network. The servercomputer 800 may connect to the network 820 through a network interfaceunit 804 connected to the system bus 822. It should be appreciated thatthe network interface unit 804 may also be utilized to connect to othertypes of networks and remote computing systems. The server computer 800also includes an input/output controller 806 for receiving andprocessing input from a number of other devices, including the userinterface 116 generated on the user device 104 which could include atouch user interface display screen, or another type of input device, asdescribed above. Similarly, the input/output controller 806 may provideoutput to a touch user interface display screen or other type of outputdevice.

As mentioned briefly above, the mass storage device 814 and the RAM 810of the server computer 800 can store software instructions and data. Thesoftware instructions include an operating system 818 suitable forcontrolling the operation of the server computer 800. The mass storagedevice 814 and/or the RAM 810 also store software instructions, thatwhen executed by the CPU 802, cause the server computer 800 to providethe functionality of the server computer 800 discussed in this document.For example, when the server computer 800 corresponds to the FI server102, the mass storage device 814 and/or the RAM 810 can store softwareinstructions that, when executed by the CPU 802, cause the servercomputer 800 to implement the system subscription module 109, thebehavior monitoring module 110, the trigger module 112, the confirmationmodule 113, the action module 114, the execution module 115, and anyother modules incorporated to perform the various functionalitiesdescribed.

Although various embodiments are described herein, those of ordinaryskill in the art will understand that many modifications may be madethereto within the scope of the present disclosure. Accordingly, it isnot intended that the scope of the disclosure in any way be limited bythe examples provided.

What is claimed is:
 1. A system for facilitating one or more financialactions, the system comprising: a plurality of positioning devices, eachrespective positioning device of the plurality of positioning deviceshaving a known location and a proximity sensor to track mobile devicesbased on proximity of the mobile devices to the respective positioningdevice; at least one processor; and memory encoding instructions that,when executed by the at least one processor, causes the at least oneprocessor to: monitor a user's behavior over a period of time inconnection with one or more predefined triggering events, the one ormore predefined triggering events comprising a new behavior pattern or adeviation from a previous behavior pattern and being selected from:personal relationship changes of the user; employment changes of theuser or a family member of the user or a person living with the user;residence changes of the user or a family member of the user or a personliving with the user; new purchases that exceed a predefined thresholdpurchase amount; and new purchases that require multiple payments overtime, wherein monitoring the user's behavior over the period of time inconnection with the one or more predefined triggering events includesto: collect a plurality of location data blocks over the period of time,each respective location data block storing the user's physical locationat a point in time based on monitoring the plurality of positioningdevices to track a mobile device associated with the user over theperiod of time based on proximity of the mobile device associated withthe user to one or more of the plurality of positioning devices; andassign, to each respective location data block of the plurality oflocation data blocks, a respective relevance value indicating apredictive value of the respective location data block in connectionwith at least one of the one or more predefined triggering events;infer, based on data collected from the monitoring, an occurrence of atleast one of the one or more predefined triggering events responsive toa sum of relevance values of the plurality of location data blockscollected in connection with the at least one of the one or morepredefined triggering events that meets or exceeds a predefinedthreshold relevance value; notify the user of the at least one inferredtriggering event; invite the user to take one or more financial actionsrelated to the at least one inferred triggering event; and in responseto a selection of the user to take at least one of the one or morefinancial actions, execute at least one of the one or more financialactions.
 2. The system of claim 1, wherein, before the invite, theinstructions cause the at least one processor to generate one or moreconfirmation questions and process answers of the user to the one ormore confirmation questions confirming or disconfirming the at least oneinferred triggering event.
 3. The system of claim 1, wherein the one ormore financial actions are selected from: changing information regardingone or more financial accounts of the user; setting up automatic billpayments; sharing bill payments; and opening one or more financialaccounts.
 4. The system of claim 1, wherein the one or more financialactions the user is invited to take are determined partially based oninformation received from the user about the at least one inferredtriggering event after the user is notified about the at least oneinferred triggering event.
 5. The system of claim 1, wherein theinstructions cause the at least one processor to identify asocioeconomic group associated with the user, and wherein the one ormore financial actions the user is invited to take are determinedpartially based on financial actions taken by one or more people in thesocioeconomic group other than the user.
 6. The system of claim 1,wherein the user's behavior is monitored using one or more trackingdevices selected from: motion tracking devices; web activity trackingdevices; spending tracking devices; and social media tracking devices.7. The system of claim 1, wherein monitoring the user's behavior overthe period of time in connection with the one or more predefinedtriggering events further includes to: decrease a relevance value of atleast one of the plurality of location data blocks over the period oftime; and adjust a relevance value of at least one of the plurality oflocation data blocks based on a repetition of the existence of the thirdlocation data block.
 8. The system of claim 1, wherein monitoring theuser's behavior over the period of time in connection with the one ormore predefined triggering events further includes to: modify arelevance value of at least one of the plurality of location data blocksbased on a new interaction by the user, thereby increasing thespecificity of the second location data block.
 9. A computer implementedmethod, comprising: monitoring a user's behavior over a period of timein connection with one or more predefined triggering events, the one ormore predefined triggering events comprising a new behavior pattern or adeviation from a previous behavior pattern, the monitoring comprising:collecting data blocks in connection with the one or more predefinedtriggering events, wherein each of the data blocks is assigned arelevance value between a negative number and a positive number, therelevance value indicating a predictive value of a data block inconnection with at least one of the one or more predefined triggeringevents, wherein collecting the data blocks includes: collecting aplurality of location data blocks over the period of time, eachrespective location data block of the plurality of location data blocksstoring the user's physical location at a point in time based onmonitoring a plurality of positioning devices to track a mobile deviceassociated with the user over the period of time based on proximity ofthe mobile device associated with the user to one or more of theplurality of positioning devices; and assigning, to each respectivelocation data block of the plurality of location data blocks, arespective relevance value indicating a predictive value of therespective location data block in connection with at least one of theone or more predefined triggering events; inferring, based on the datablocks collected from the monitoring, an occurrence of at least one ofthe one or more predefined triggering events based on a sum of referencevalues of the data blocks meeting or exceeding a threshold; notifyingthe user of the at least one inferred triggering event; inviting theuser to take one or more financial actions related to the at least oneinferred triggering event; and in response to a selection of the user totake at least one of the one or more financial actions, executing atleast one of the one or more financial actions.
 10. The method of claim9, wherein the one or more predefined triggering events are selectedfrom: personal relationship changes of the user; employment changes ofthe user or a family member of the user or a person living with theuser; residence changes of the user or a family member of the user or aperson living with the user; new purchases that exceed a predeterminedthreshold purchase amount; and new purchases that require multiplepayments over time.
 11. The method of claim 9 wherein the inferringoccurs when a sum of relevance values of the data blocks collected inconnection with a first of the at least one inferred triggering eventmeets or exceeds a predefined threshold relevance value for the first ofthe at least one triggering event.
 12. The method of claim 9, furthercomprising: generating one or more confirmation questions; andprocessing answers of the user to the one or more confirmation questionsconfirming or disconfirming the at least one inferred triggering event,wherein the generating of the one or more confirmation questions and theprocessing of the answers are performed before the inviting.
 13. Themethod of claim 9, wherein the one or more financial actions areselected from: changing information regarding one or more financialaccounts of the user; setting up automatic bill payments; sharing billpayments; and opening one or more financial accounts.
 14. The method ofclaim 9, wherein the one or more financial actions of the inviting stepare determined partially based on information received from the userabout the at least one inferred triggering event after the notifyingstep.
 15. The method of claim 9, further comprising: identifying asocioeconomic group associated with the user, wherein the one or morefinancial actions the user is invited to take are determined partiallybased on financial actions taken by one or more people in thesocioeconomic group other than the user.
 16. A non-transitorycomputer-readable data storage medium storing instructions that, whenexecuted by a processor, cause the processor to: monitor a user'sbehavior over a period of time in connection with one or more predefinedtriggering events, the one or more predefined triggering eventscomprising a new behavior pattern or a deviation from a previousbehavior pattern and being selected from: personal relationship changesof the user; employment changes of the user or a family member of theuser or a person living with the user; residence changes of the user ora family member of the user or a person living with the user; newpurchases that exceed a predefined threshold purchase amount; and newpurchases that require multiple payments over time, wherein monitoringthe user's behavior over the period of time in connection with the oneor more predefined triggering events includes to: collect a plurality oflocation data blocks over the period of time, each respective locationdata block of the plurality of location data blocks storing the user'sphysical location at a respective point in time based on monitoring aplurality of positioning devices to track a mobile device associatedwith the user over the period of time based on proximity of the mobiledevice associated with the user to one or more of the plurality ofpositioning devices; and assign, to each respective location data block,a respective relevance value indicating a predictive value of therespective location data block in connection with at least one of theone or more predefined triggering events; infer, based on data collectedfrom the monitoring, an occurrence of at least one of the one or morepredefined triggering events; notify the user of the at least oneinferred triggering event; invite the user to take one or more financialactions related to the at least one inferred triggering event; and inresponse to a selection of the user to take at least one of the one ormore financial actions, execute at least one of the one or morefinancial actions.
 17. The non-transitory computer-readable data storagemedium of claim 16, wherein the one or more financial actions areselected from: changing information regarding one or more financialaccounts of the user; setting up automatic bill payments; sharing billpayments; and opening one or more financial accounts.
 18. Thenon-transitory computer-readable data storage medium of claim 16,wherein the one or more financial actions the user is invited to takeare determined partially based on information received from the userabout the at least one inferred triggering event after the user isnotified about the at least one inferred triggering event.
 19. Thenon-transitory computer-readable data storage medium of claim 16,wherein the relevance values have a value between a negative number anda positive number.
 20. The non-transitory computer-readable data storagemedium of claim 16, wherein the inferring of a first of the at least onetriggering event occurs when a sum of relevance values of the datablocks collected in connection with the first of the at least onetriggering event meets or exceeds a predefined threshold relevancevalue.